74 lines
2.5 KiB
Python
74 lines
2.5 KiB
Python
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import numpy as np
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import pytest
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from numpy.testing import assert_array_equal
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from sklearn.utils._encode import _unique
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from sklearn.utils._encode import _encode
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from sklearn.utils._encode import _check_unknown
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@pytest.mark.parametrize(
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"values, expected",
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[(np.array([2, 1, 3, 1, 3], dtype='int64'),
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np.array([1, 2, 3], dtype='int64')),
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(np.array(['b', 'a', 'c', 'a', 'c'], dtype=object),
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np.array(['a', 'b', 'c'], dtype=object)),
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(np.array(['b', 'a', 'c', 'a', 'c']),
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np.array(['a', 'b', 'c']))],
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ids=['int64', 'object', 'str'])
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def test_encode_util(values, expected):
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uniques = _unique(values)
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assert_array_equal(uniques, expected)
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encoded = _encode(values, uniques=uniques)
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assert_array_equal(encoded, np.array([1, 0, 2, 0, 2]))
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def test_encode_with_check_unknown():
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# test for the check_unknown parameter of _encode()
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uniques = np.array([1, 2, 3])
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values = np.array([1, 2, 3, 4])
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# Default is True, raise error
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with pytest.raises(ValueError,
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match='y contains previously unseen labels'):
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_encode(values, uniques=uniques, check_unknown=True)
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# dont raise error if False
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_encode(values, uniques=uniques, check_unknown=False)
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# parameter is ignored for object dtype
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uniques = np.array(['a', 'b', 'c'], dtype=object)
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values = np.array(['a', 'b', 'c', 'd'], dtype=object)
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with pytest.raises(ValueError,
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match='y contains previously unseen labels'):
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_encode(values, uniques=uniques, check_unknown=False)
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@pytest.mark.parametrize("values, uniques, expected_diff, expected_mask", [
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(np.array([1, 2, 3, 4]),
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np.array([1, 2, 3]),
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[4],
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[True, True, True, False]),
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(np.array([2, 1, 4, 5]),
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np.array([2, 5, 1]),
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[4],
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[True, True, False, True]),
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(np.array(['a', 'b', 'c', 'd'], dtype=object),
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np.array(['a', 'b', 'c'], dtype=object),
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np.array(['d'], dtype=object),
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[True, True, True, False]),
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(np.array(['d', 'c', 'a', 'b'], dtype=object),
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np.array(['a', 'c', 'b'], dtype=object),
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np.array(['d'], dtype=object),
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[False, True, True, True])
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])
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def test_check_unknown(values, uniques, expected_diff, expected_mask):
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diff = _check_unknown(values, uniques)
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assert_array_equal(diff, expected_diff)
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diff, valid_mask = _check_unknown(values, uniques, return_mask=True)
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assert_array_equal(diff, expected_diff)
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assert_array_equal(valid_mask, expected_mask)
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